Marco Riva

130 papers receiving 2.9k citations

Peers

Marco Riva
Comparison fields: 5 of 136
  • Genetics 856
  • Radiology, Nuclear Medicine and Imaging 721
  • Cognitive Neuroscience 592
  • Neurology 159
  • Biophysics 103
Replace Loukas G. Astrakas with:
Loukas G. Astrakas Greece
Kyousuke Kamada Japan
Andrew Brodbelt United Kingdom
Kaan Yağmurlu United States
Guangbin Cui China
Robert W. Prost United States
Erik H. Middlebrooks United States
Donald A. Ross United States
Andrew W. McEvoy United Kingdom
Francisco González Spain
Marco Riva relative to Loukas G. Astrakas Greece Loukas G. Astrakas's profile →
Citations per field
00.5×2.9×
Loukas G. Astrakas · 1×
Citations per year

Countries citing papers authored by Marco Riva

Since Specialization
Citations

This map shows the geographic impact of Marco Riva's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Marco Riva with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marco Riva more than expected).

Fields of papers citing papers by Marco Riva

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Marco Riva. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Marco Riva. The network helps show where Marco Riva may publish in the future.

Co-authors

The 25 scholars most cited alongside Marco Riva, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Marco Riva Line = papers co-authored together Marco Riva links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 141 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011191
2 2010118
3 2011113
4 2014100
5 201789
6 202083
7 201283
8 201381
9 202166
10
In vivo detection of cortical plaques by MR imaging in patients with multiple sclerosis.
200763
11 201761
12 201761
13 201856
14 201954
15 201453
16 201650
17 201647
18 201846
19 201946
20 200542

About Marco Riva

Marco Riva is a scholar working on Genetics, Surgery, Radiology, Nuclear Medicine and Imaging, Epidemiology and Cognitive Neuroscience, having authored 141 papers that have together received 3.0k indexed citations. Recurring topics across this work include Glioma Diagnosis and Treatment (40 papers), Advanced Neuroimaging Techniques and Applications (18 papers), Meningioma and schwannoma management (16 papers), Neurobiology of Language and Bilingualism (9 papers), Brain Metastases and Treatment (8 papers), Spine and Intervertebral Disc Pathology (6 papers), Pituitary Gland Disorders and Treatments (5 papers) and Advanced MRI Techniques and Applications (5 papers). The work is most often cited by research in Genetics (856 citations), Radiology, Nuclear Medicine and Imaging (721 citations), Cognitive Neuroscience (592 citations), Neurology (159 citations) and Biophysics (103 citations). Marco Riva has collaborated with scholars based in Italy, United States and United Kingdom. Frequent co-authors include Lorenzo Bello, Antonella Castellano, Alessandra Casarotti, Andrea Falini, Enrica Fava, Federico Pessina, Marco Rossi, Costanza Papagno, Alessandro Comi and Marco Conti Nibali. Their work appears in journals such as Neuro-Oncology, Journal of neurosurgery, World Neurosurgery, Neurological Sciences and Human Brain Mapping.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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